Association and resource partitioning in a wireless network with relays

ABSTRACT

Techniques for performing association and resource partitioning in a wireless network with relays are described. In an aspect, resource partitioning may be performed to allocate available resources to nodes and access/backhaul links of relays. In one design, a node computes local metrics for a plurality of possible actions related to resource partitioning. The node receives local metrics for the possible actions from at least one neighbor node and determines overall metrics for the possible actions based on the computed and received local metrics. The node determines resources allocated to a set of nodes and resources allocated to the access and backhaul links of at least one relay based on the overall metrics for the possible actions. In another aspect, association involving relays may be performed by taking into account the performance of the relays. In yet another aspect, association and resource partitioning may be performed jointly.

The present application is a divisional application of U.S. applicationSer. No. 12/725,146, entitled “ASSOCIATION AND RESOURCE PARTITIONING INHETEROGENEOUS NETWORKS WITH RELAYS,” filed Mar. 16, 2010 and now patentU.S. Pat. No. 8,553,711, issued Oct. 8, 2013, which claims priority toProvisional U.S. Application Ser. No. 61/161,653, entitled “ASSOCIATIONAND RESOURCE PARTITIONING IN HETEROGENEOUS NETWORKS WITH RELAYS,” filedMar. 19, 2009, all assigned to the assignee hereof and incorporatedherein by reference.

BACKGROUND

I. Field

The present disclosure relates generally to communication, and morespecifically to techniques for supporting wireless communication.

II. Background

Wireless communication networks are widely deployed to provide variouscommunication content such as voice, video, packet data, messaging,broadcast, etc. These wireless networks may be multiple-access networkscapable of supporting multiple users by sharing the available networkresources. Examples of such multiple-access networks include CodeDivision Multiple Access (CDMA) networks, Time Division Multiple Access(TDMA) networks, Frequency Division Multiple Access (FDMA) networks,Orthogonal FDMA (OFDMA) networks, and Single-Carrier FDMA (SC-FDMA)networks.

A wireless communication network may include a number of base stationsthat can support communication for a number of user equipments (UEs). AUE may communicate with a base station via the downlink and uplink. Thedownlink (or forward link) refers to the communication link from thebase station to the UE, and the uplink (or reverse link) refers to thecommunication link from the UE to the base station.

The wireless network may also include relays to improve coverage andcapacity of the wireless network. A relay may communicate with a basestation on a backhaul link and may appear as a UE to the base station.The relay may also communicate with one or more UEs on an access linkand may appear as a base station to the UE(s). The relay utilizesresources in order to communicate with the base station and the UE(s).It may be desirable to support efficient operation of the relay.

SUMMARY

Techniques for performing association and resource partitioning in awireless network with relays are described herein. Association refers toa process to determine a serving node for a station. A node may be abase station or a relay, and a station may be a UE or a relay. Resourcepartitioning refers to a process to allocate available resources tonodes. Resource partitioning may also be used to allocate resourcesbetween the access link and backhaul link of relays. Association mayalso be referred to as server selection. Resource partitioning may alsobe referred to as resource allocation, resource coordination, etc.

In an aspect, resource partitioning may be performed to allocateavailable resources to a set of nodes and to the access and backhaullinks of at least one relay. In one design, a node in the set of nodesmay compute local metrics for a plurality of possible actions related toresource partitioning. The node may receive local metrics for theplurality of possible actions from at least one neighbor node and maydetermine overall metrics for the possible actions based on the computedlocal metrics and the received local metrics. The node may determineresources allocated to the set of nodes and resources allocated to theaccess and backhaul links of the at least one relay based on the overallmetrics for the possible actions.

In another aspect, association may be performed by taking into accountthe performance of relays. In one design, metrics for a plurality ofpossible actions related to association involving at least one relay maybe obtained. The plurality of possible actions may include (i) possibleactions for handing out one or more stations from a node to neighbornodes and/or (ii) possible actions for handing in one or more stationsfrom the neighbor nodes to the node. At least one serving node for atleast one station may be determined based on the metrics for theplurality of possible actions. The at least one serving node and the atleast one station may comprise the at least one relay. In one design,metrics (e.g., rates) for a relay may be computed based on resourcesallocated to the access and backhaul links of the relay and/or based onan access capacity and a backhaul capacity of the relay. The metrics maybe used to select the at least one serving node for the at least onestation.

In yet another aspect, association and resource partitioning may beperformed jointly, e.g., by computing metrics for a plurality ofpossible actions related to association and resource partitioning. Inone design, serving nodes be selected for stations and availableresources may be allocated to nodes and to access and backhaul links byevaluating different possible associations between stations and nodes,different possible allocations of resources to nodes, and differentpossible allocations of resources to the access and backhaul links.

Various aspects and features of the disclosure are described in furtherdetail below.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a wireless communication network.

FIG. 2 shows communication between a base station and a UE via a relay.

FIG. 3 shows partitioning of resources between the access and backhaullinks.

FIG. 4 shows access capacity and backhaul capacity of a relay.

FIG. 5 shows a process for performing association and resourcepartitioning.

FIGS. 6 and 7 show a process and an apparatus, respectively, forsupporting communication with unified resource partitioning for nodesand access/backhaul links.

FIG. 8 shows a process for performing unified resource partitioning,

FIGS. 9 and 10 show a process and an apparatus, respectively, forsupporting communication with association involving relays.

FIGS. 11 and 12 show a process and an apparatus, respectively, forsupporting communication by a relay.

FIGS. 13 and 14 show a process and an apparatus, respectively, forcommunicating by a UE.

FIG. 15 shows a block diagram of a node and a station.

DETAILED DESCRIPTION

The techniques described herein may be used for various wirelesscommunication networks such as CDMA, TDMA, FDMA, OFDMA, SC-FDMA andother networks. The terms “network” and “system” are often usedinterchangeably. A CDMA network may implement a radio technology such asUniversal Terrestrial Radio Access (UTRA), cdma2000, etc. UTRA includesWideband CDMA (WCDMA) and other variants of CDMA. cdma2000 coversIS-2000, IS-95 and IS-856 standards. A TDMA network may implement aradio technology such as Global System for Mobile Communications (GSM).An OFDMA network may implement a radio technology such as Evolved UTRA(E-UTRA), Ultra Mobile Broadband (UMB), IEEE 802.11 (Wi-Fi), IEEE 802.16(WiMAX), IEEE 802.20, Flash-OFDM®, etc. UTRA and E-UTRA are part ofUniversal Mobile Telecommunication System (UMTS). 3GPP Long TermEvolution (LTE) and LTE-Advanced (LTE-A) are new releases of UMTS thatuse E-UTRA, which employs OFDMA on the downlink and SC-FDMA on theuplink. UTRA, E-UTRA, UMTS, LTE, LTE-A and GSM are described indocuments from an organization named “3rd Generation PartnershipProject” (3GPP). cdma2000 and UMB are described in documents from anorganization named “3rd Generation Partnership Project 2” (3GPP2). Thetechniques described herein may be used for the wireless networks andradio technologies mentioned above as well as other wireless networksand radio technologies.

FIG. 1 shows a wireless communication network 100, which may include anumber of base stations and other network entities. A base station maybe an entity that communicates with UEs and relays and may also bereferred to as a node, a Node B, an evolved Node B (eNB), an accesspoint, etc. Each base station may provide communication coverage for aparticular geographic area. In 3GPP, the term “cell” can refer to acoverage area of a base station and/or a base station subsystem servingthis coverage area, depending on the context in which the term is used.In 3GPP2, the term “sector” or “cell-sector” can refer to a coveragearea of a base station and/or a base station subsystem serving thiscoverage area. For clarity, 3GPP concept of “cell” is used in thedescription herein.

A base station may provide communication coverage for a macro cell, apico cell, a femto cell, and/or other types of cell. A macro cell maycover a relatively large geographic area (e.g., several kilometers inradius) and may allow unrestricted access by UEs with servicesubscription. A pico cell may cover a relatively small geographic areaand may allow unrestricted access by UEs with service subscription. Afemto cell may cover a relatively small geographic area (e.g., a home)and may allow restricted access by UEs having association with the femtocell (e.g., UEs in a Closed Subscriber Group (CSG)). In the exampleshown in FIG. 1, wireless network 100 includes macro base stations 110and 112 for macro cells, a pico base station 114 for a pico cell, and afemto/home base station 116 for a femto cell.

Wireless network 100 may also include relays, e.g., a relay 118. A relaymay be an entity that receives a transmission of data from an upstreamentity (e.g., a base station or a UE) and sends a transmission of thedata to a downstream entity (e.g., a UE or a base station). A relay mayalso be a UE that relays transmissions for other UEs. A relay may alsobe referred to as a node, a station, a relay station, a relay basestation, a relay node, etc.

Wireless network 100 may be a heterogeneous network that includes basestations of different types, e.g., macro base stations, pico basestations, femto base stations, relays, etc. These different types ofbase stations may have different transmit power levels, differentcoverage areas, and different impact on interference in wireless network100. For example, macro base stations may have a high transmit powerlevel (e.g., 20 Watts or 43 dBm), pico base stations and relays may havea lower transmit power level (e.g., 2 Watts or 33 dBm), and femto basestations may have a low transmit power level (e.g., 0.2 Watts or 23dBm). Different types of base stations may belong in different powerclasses having different maximum transmit power levels.

A network controller 130 may couple to a set of base stations and mayprovide coordination and control for these base stations. Networkcontroller 130 may communicate with base stations via a backhaul. Thebase stations may also communicate with one another via the backhaul.

UEs 120 may be dispersed throughout wireless network 100, and each UEmay be stationary or mobile. A UE may also be referred to as a station,a terminal, a mobile station, a subscriber unit, etc. A UE may be acellular phone, a personal digital assistant (PDA), a wireless modem, awireless communication device, a handheld device, a laptop computer, acordless phone, a wireless local loop (WLL) station, etc. A UE may beable to communicate with base stations, relays, other UEs, etc.

FIG. 2 shows communication between base station 110 and UE 120 via relay118. Relay 118 may communicate with base station 110 via a backhaul linkand may communicate with UE 120 via an access link. On the backhaullink, relay 118 may receive downlink transmissions from base station 110via a backhaul downlink and may send uplink transmission to base station110 via a backhaul uplink. On the access link, relay 118 may senddownlink transmissions to UE 120 via an access downlink and may receiveuplink transmission from UE 120 via an access uplink.

The wireless network may support a set of resources for each of thedownlink and uplink. The available resources may be defined based ontime, or frequency, or both time and frequency, or some other criteria.For example, the available resources may correspond to differentfrequency subbands, or different time interlaces, or differenttime-frequency blocks, etc. A time interlace may include evenly spacedtime slots, e.g., every S-th time slot, where S may be any integervalue. The available resources may be defined for the entire wirelessnetwork.

Relay 118 typically cannot transmit and receive on the same frequencychannel at the same time. Hence, some of the available resources for thedownlink may be allocated for the access link and may be referred to asdownlink access resources. Relay 118 may send downlink transmissions toUE 120 on the downlink access resources and may receive downlinktransmissions from base station 110 on the remaining downlink resources.Similarly, some of the available resources for the uplink may beallocated for the access link and may be referred to as uplink accessresources. Relay 118 may receive uplink transmissions from UE 120 on theuplink access resources and may send uplink transmissions to basestation 110 on the remaining uplink resources. For clarity, much of thedescription below is for transmission on the downlink.

FIG. 3 shows exemplary partitioning of the available resources for thedownlink between the backhaul link and the access link of relay 118. Kresources with indices of 1 through K may be available for the downlink,where K may be any integer value. In the example shown in FIG. 3,resources 2, 5, . . . , K are allocated for the access downlink. Relay118 may transmit to its UEs (or relay UEs) on resources 2, 5, . . . , Kand may listen for transmissions from serving base station 110 on theremaining downlink resources. Base station 110 may transmit to its UEs(or macro UEs) on resources 2, 5, . . . , K and may transmit to its UEsand/or relay 118 on the remaining resources.

In the description herein, a node may be a base station or a relay. Abase station may be a macro base station, a pico base station, a femtobase station, etc. A node serving a relay is referred to as a servingnode of the relay. A node serving a UE is referred to as a serving nodeof the UE. A station is an entity that communicates with a node. Astation may be a UE or a relay. In one scenario, a station may be a UE,and a node may be a base station or a relay. In another scenario, astation may be a relay, and a node may be a base station.

In an aspect, unified resource partitioning may be performed to allocatethe available resources for a given link (e.g., the downlink or uplink)to a set of nodes and to the access and backhaul links of one or morerelays. Unified resource partitioning may thus cover both (i) resourcepartitioning to allocate the available resources to the set of nodes,e.g., to mitigate interference, and (ii) resource partitioning toallocate resources between the access and backhaul links of therelay(s). Unified resource partitioning for nodes and access/backhaullinks may improve performance due to inter-dependency between relays andtheir serving nodes. In particular, scheduling decisions of a relay mayaffect the performance of its serving node and possibly other nodes.Similarly, scheduling decisions of a serving node may affect theperformance of its relay(s) and other nodes. Improved performance may beachieved by concurrently performing (i) resource partitioning toallocate the available resources to the set of nodes and (ii) resourcepartitioning between the access and backhaul links of relay(s). Unifiedresource partitioning for nodes and access/backhaul links may beperformed as described below.

A station (e.g., a UE or a relay) may be located within the coverage ofone or more nodes. In one design, a single node may be selected to servethe station on both the downlink and uplink. In another design, one nodemay be selected to serve the station on each of the downlink and uplink.For both designs, a serving node may be selected for the station basedon a metric such as maximum geometry/signal strength, minimum pathloss,maximum energy/interference efficiency, maximum user throughput, etc.Geometry relates to received signal quality, which may be quantified bya carrier-over-thermal (CoT), a signal-to-noise ratio (SNR), asignal-to-noise-and-interference ratio (SINR), a carrier-to-interferenceratio (C/I), etc. Maximizing energy/interference efficiency may entail(i) minimizing a required transmit energy per bit or (ii) minimizing areceived interference energy per unit of received useful signal energy.Part (ii) may correspond to maximizing the ratio of channel gain for anintended node to a sum of channel gains for all interfered nodes.Maximizing user throughput may take into account various factors such asthe loading of a node (e.g., the number of stations currently served bythe node), the amount of resources allocated to the node, the availablebackhaul capacity of the node, etc.

Association may be performed for a station when it is first powered onand may be referred to as initial association. Association may also beperformed to select a new serving node for handover of the station.

In another aspect, association involving one or more relays may beperformed by taking into account the performance of the relay(s).Association involving a relay may cover (i) selecting a serving node forthe relay or (ii) determining whether to select the relay as a servingnode for a UE. In either case, the performance of the relay may bedetermined based on characteristics of the relay (e.g., the resourcesallocated to the access and backhaul links of the relay) and may be usedfor server selection.

Resource partitioning and association may be related, and one may affectthe other. For example, a new association between a station and a nodemay shift loading from one node to another node and may trigger/requireresource partitioning, e.g., to address high interference due to linkimbalance or restricted association. Conversely, resource partitioningmay affect signal and interference conditions on different resources,which may affect metrics used for determining association. For example,metrics such as downlink geometry may no longer be indicative of signalquality on all resources due to changes in signal and interferenceconditions resulting from resource partitioning. Furthermore, resourcepartitioning may affect the amount of available resources for nodes andmay be affected by cell loading.

In yet another aspect, association and resource partitioning may beperformed jointly. For joint association and resource partitioning,serving nodes may be selected for stations and available resources maybe allocated to nodes and to access and backhaul links by consideringdifferent possible associations between stations and nodes, differentpossible allocations of resources to nodes, and different possibleallocations of resources to the access and backhaul links. This mayallow association to take into account current resource partitioning andloading, allow resource partitioning to be updated based on associationupdates, and allow association to be updated based on changes inresource partitioning and/or other association updates.

In one design, association and/or resource partitioning may be performedin a centralized manner. In this design, a designated entity may receivepertinent information for stations and nodes, compute metrics forassociation and/or resource partitioning, and select the bestassociation and/or resource partitioning based on the computed metrics.In another design, association and/or resource partitioning may beperformed in a distributed manner by a set of nodes. In this design,each node may compute certain metrics and may exchange metrics withneighbor nodes. Each node may then determine and select the associationand/or resource partitioning that can provide the best performance.

Association and/or resource partitioning may be performed for only thedownlink, or only the uplink, or both the downlink and uplink. Resourcepartitioning may be performed in different manners for the downlink anduplink. For clarity, joint association and resource partitioning for thedownlink is described in detail below.

Table 1 lists a set of components that may be used for joint associationand resource partitioning for the downlink.

TABLE 1 Component Description Active Set A set of nodes maintained for agiven station t and denoted as AS(t). Neighbor Set A set of nodesmaintained for a given node p and denoted as NS(p). Resources Timeand/or frequency resources that may be allocated to nodes. Transmit PSDA set of transmit power spectral density (PSD) levels Levels that may beused for any given resource by a node. Utility A function used toquantify the performance of differ- Function ent possible associationand resource partitioning.

In one design, an active set may be maintained for each station and maybe determined based on pilot measurements made by the station and/orpilot measurements made by nodes. An active set for a given station tmay include nodes that (i) have non-negligible contribution to signal orinterference observed by station t on the downlink and/or (ii) receivenon-negligible signal or interference from station t on the uplink. Inone design, a node may be included in the active set of station t if theCoT of this node is greater than a threshold of CoT_(min). A node mayalso be included in the active set based on received signal strengthand/or other criteria. The active set may be limited (e.g., to Nstrongest nodes, where N may be any suitable value) in order to reducecomputation complexity for association and/or resource partitioning.

In one design, a neighbor set may be maintained for each node and mayinclude nodes that participate in association and/or resourcepartitioning. The neighbor set for each node may be determined based onactive sets of stations. In one design, a neighbor set for a given nodep may include (i) nodes that are in the active sets of stations servedby node p and (ii) nodes serving stations that have node p in theiractive sets. The neighbor set may thus include node p and its neighbornodes. The neighbor set may be limited in order to reduce computationcomplexity for association and/or resource partitioning.

A neighbor set may be formed in various manners when relays are present.In a first neighbor set design, a neighbor set may include nodescorresponding to base stations as well as relays. In this design,metrics may be computed for each node (including each relay) in theneighbor set and used for association and/or resource partitioning. In asecond neighbor set design, a neighbor set may include nodescorresponding to base stations but not relays. In this design, metricsmay be computed for serving nodes of relays and may account for theeffects of the relays. For both designs, a neighbor set may includenodes that are neighbors of a relay even though these nodes may not beneighbors of one another. For example, a given relay z may be served bya serving node s and may be within range of another node q, with nodes sand q not being within range of one another. A neighbor set for node smay include node q due to potential effects from relay z. Similarly, aneighbor set for node q may include node s due to potential effects fromrelay z. For the first neighbor set design, if serving node s isincluded in a neighbor set of another node, then relay z may also beincluded in the neighbor set. A neighbor set may also be defined inother manners.

In one design, a set of transmit PSD levels may be defined for each nodeand may include all transmit PSD levels that can be used by the node foreach resource on the downlink. A node may use one of the transmit PSDlevels for each resource. In one design, the set of transmit PSD levelsmay include a nominal PSD level, a low PSD level, a zero PSD level, etc.The nominal PSD level on all available resources may correspond to themaximum transmit power of the node. The set of transmit PSD levels forthe node may be dependent on the power class of the node. In one design,the set of transmit PSD levels for a given power class may be the unionof the nominal PSD levels of all power classes lower than or equal tothis power class, plus zero PSD level. For example, a macro basestation/node may include a nominal PSD level of 43 dBm (for the macropower class), a low PSD level of 33 dBm (corresponding to the nominalPSD level for the pico power class), and a zero PSD level. The set oftransmit PSD levels for each power class may also be defined in othermanners.

A utility function may be used to compute local metrics and overallmetrics for association and/or resource partitioning. A local metric fora given node p may be denoted as U(p) and may be indicative of theperformance of the node for a given association and/or resourcepartitioning. An overall metric for a set of nodes, NS, may be denotedas V(NS) and may be indicative of the overall performance of the set ofnodes for a given association and/or resource partitioning.

In one design, the utility function may be defined based on a sum ofuser rates, as follows:

$\begin{matrix}{{{U(p)} = {\sum\limits_{{S{(t)}} = p}\;{R(t)}}}{and}{{{V({NS})} = {\sum\limits_{p\; \in \;{NS}}\;{U(p)}}},}} & {{Eq}\mspace{14mu}(1)}\end{matrix}$where S(t) is a serving node for station t, and

R(t) is a rate achieved by station t for node p.

In other designs, the utility function may be equal to the minimum ofuser rates, or the sum of log of user rates, or the sum of log of log ofuser rates, or the sum of −1/(user rate)³, or some other function ofrate, latency, queue size, etc.

Local metrics for each node may be computed based on the rates ofstations served by that node, e.g., as shown in equation (1). In onedesign, the rate of each station may be estimated by assuming that thestation is assigned a fraction of each available resource. This fractionmay be denoted as α(t,r) and may be viewed as the fraction of timeduring which resource r is assigned to station t. The rate for station tmay then be computed as follows:

$\begin{matrix}{{{R(t)} = {\sum\limits_{r}\;{{\alpha\left( {t,r} \right)} \cdot {{SE}\left( {t,r} \right)} \cdot {W(r)}}}},} & {{Eq}\mspace{14mu}(2)}\end{matrix}$where SE(t,r) is the spectral efficiency of station t on resource r, and

W(r) is the bandwidth of resource r.

The spectral efficiency of station t on resource r may be determined asfollows:

$\begin{matrix}{{{{SE}\left( {t,r} \right)} = {C\left( \frac{{{PSD}\left( {p,r} \right)} \cdot {G\left( {p,t} \right)}}{N_{0} + {\sum\limits_{q \neq p}\;{{{PSD}\left( {q,r} \right)} \cdot {G\left( {q,t} \right)}}}} \right)}},} & {{Eq}\mspace{14mu}(3)}\end{matrix}$where PSD(p,r) is the transmit PSD of serving node p on resource r,

PSD(q,r) is the transmit PSD of neighbor node q on resource r,

G(p,t) is the channel gain between serving node p and station t,

G(q,t) is the channel gain between neighbor node q and station t,

N₀ is ambient interference and thermal noise observed by station t, and

C( ) denotes a capacity function.

In equation (3), the numerator within the parenthesis denotes thedesired received power from serving node p at station t. The denominatordenotes the total interference from all neighbor nodes as well as N₀ atstation t. The transmit PSD used by nodes p and q on resource r may beknown from the current resource partitioning. The channel gains fornodes p and q may be obtained based on pilot measurements from stationt. N₀ may be measured/estimated by UE t and included in the computation,or may be reported by UE t to the wireless network (e.g., to servingnode p), or may be ignored (e.g., when the computation is done by nodep). The capacity function may be a constrained capacity function, anunconstrained capacity function, etc.

A pre-scheduler for each node may perform scheduling forecast and maymaximize the utility function over the space of the α(t,r) parameter, asfollows:

$\begin{matrix}{{{maximize}\mspace{14mu}{U(p)}},\mspace{14mu}{{{for}\mspace{14mu} 0} \leq {\alpha\left( {t,r} \right)} \leq {1\mspace{14mu}{and}\mspace{14mu}{\sum\limits_{{S{(t)}} = p}^{\;}\;{\alpha\left( {t,r} \right)}}} \leq 1.}} & {{Eq}\mspace{14mu}(4)}\end{matrix}$Equation (4) shows a convex optimization on the α(t,r) parameter and maybe solved numerically.

The rate for station t may be constrained as follows:R(t)≦R _(max)(t),  Eq (5)where R_(max)(t) is the maximum rate supported by station t.

The overall rate R(p) for node p may also be constrained as follows:

$\begin{matrix}{{{R(p)} = {{\sum\limits_{{S{(t)}} = p}^{\;}\;{R(t)}} \leq {R_{BH}(p)}}},} & {{Eq}\mspace{14mu}(6)}\end{matrix}$where R_(BH)(p) is a backhaul capacity of node p.

Different types of nodes may have different backhaul capacities. Thebackhaul capacity of a base station may be a fixed value whereas thebackhaul capacity of a relay may be a variable value, which may bedependent on the access/backhaul partitioning for the relay. Thebackhaul capacity of node p may be sent to neighbor nodes via thebackhaul and/or over the air for association decisions.

FIG. 4 shows access capacity and backhaul capacity of a given relay z.In the example shown in FIG. 4, relay z serves M stations 1′ through M′on resources allocated to the access downlink by the resourcepartitioning under consideration. Relay z obtains rates of R(1′) throughR(M′) for these M stations. The access capacity of relay z may becomputed as follows:

$\begin{matrix}{{{R_{AC}(z)} = {\sum\limits_{{S{(t^{\prime})}} = z}^{\;}\;{R\left( t^{\prime} \right)}}},} & {{Eq}\mspace{14mu}(7)}\end{matrix}$where R(t′) is the rate achieved by station t′ for relay z, and

R_(AC)(z) is the access capacity of relay z.

In the example shown in FIG. 4, serving node s serves L stations 1through L as well as relay z on resources allocated to node s by theresource partitioning under consideration. Serving node s obtains ratesof R(1) through R(L) for these L stations and a rate of R(z) for relayz. The rate for each station and the rate for relay z may be computed asshown in equations (2) and (3). However, relay z is not scheduled byserving node s on resources allocated to the access downlink, sincerelay z may transmit to its stations on these resources. Hence, theα(z,r) parameter for relay z may be set to zero for each resourceallocated to the access downlink, and the rate R(z,r) for relay z oneach such resource will be zero. For the example shown in FIG. 3, relayz is not scheduled by serving node s on resources 2, 5, . . . , K andhas a rate of zero for each of these resources.

Serving node s may obtain a rate of R(z) for relay z on all resources.The backhaul capacity of relay z may then be given as follows:R _(BH)(z)=R(z),  Eq (8)where R_(BH)(z) is the backhaul capacity of relay z.

As shown in FIG. 4, the access and backhaul capacities of relay z may bedynamic and dependent on the resource partitioning under consideration.Ideally, the access capacity of relay z should be equal to the backhaulcapacity of relay z. If the access capacity is greater than the backhaulcapacity, then the total rate achieved by relay z would be limited bythe backhaul capacity, and some resources allocated to the access linkmay be under-utilized. The total rate for all stations served by relay zmay be limited by the backhaul capacity, as follows:

$\begin{matrix}{{\sum\limits_{{S{(t^{\prime})}} = z}^{\;}\;{R\left( t^{\prime} \right)}} \leq {{R_{BH}(z)}.}} & {{Eq}\mspace{14mu}(9)}\end{matrix}$

Conversely, if the access capacity is less than the backhaul capacity,then the total rate achieved by relay z would be limited by the accesscapacity, and some resources allocated to the backhaul downlink may beunder-utilized. The rate for relay z may be limited based on the accesscapacity, as follows:R(z)≦R _(AC)(z).  Eq (10)The limited rate from equation (10) may be used to compute local metricsfor serving node s. Limiting the rate of relay z as shown in equation(10) may result in more accurate local metrics for serving node s.

The backhaul capacity of relay z may be matched to the access capacityof relay z as follows. First, serving node s may perform pre-schedulingby assuming no access limitation at relay z (i.e., infinite accesscapacity) and may obtain rate R(z) as the backhaul capacity of relay z.Relay z may also perform pre-scheduling by assuming no backhaullimitation (i.e., infinite backhaul capacity) and may sum the rates ofall stations served by relay z to obtain the access capacity of relay z.Next, serving node s may send the backhaul capacity to relay z, whichmay also send the access capacity to serving node s. If the accesscapacity is less than the backhaul capacity, then serving node s mayperform pre-scheduling again with the new access capacity constraint.Conversely, if the backhaul capacity is less than the access capacity,then relay z may perform pre-scheduling again with the new backhaulcapacity constraint. Alternatively, the processing described above maybe performed iteratively by one node at a time.

The pre-scheduler for each node may perform scheduling forecast and maybe different from an actual scheduler, which may maximize a marginalutility in each scheduling interval. In one design, the pre-schedulerfor serving node s may treat relay z as one station served by node s. Inanother design, the pre-scheduler may take into account the number ofstations served by relay z for improved fairness. For example, if relayz is serving M stations with a total rate of R(z), then thepre-scheduler may model relay z as M stations each with a rate ofR(z)/M. This may result in relay z being allocated more resources if theutility function is based on the log of user rates or some othernonlinear function of user rates.

Station t (e.g., a UE or a relay) may be served by node p and may haveits rate taken into account in the computation of local metrics for nodep, e.g., as shown in equation (1). For association, station t may behanded over from node p to another node, e.g., in the neighbor set. Inone design, a spectral efficiency SE(t,q,r) may be estimated for stationt on each resource r for each candidate node q to which station t mightbe handed over. This spectral efficiency may be estimated as shown inequation (3) based on the current transmit PSD levels and the channelgains of all nodes in the active set of station t on resource r. Therate R(t,q) achieved by station t for candidate node q may then beestimated as:

$\begin{matrix}{{{R\left( {t,q} \right)} = \frac{\min\left( {{\sum\limits_{r}\;{{{SE}\left( {t,q,r} \right)} \cdot {W(r)}}},{R_{BH}(q)}} \right)}{{N(q)} + 1}},} & {{Eq}\mspace{14mu}(11)}\end{matrix}$where N(q) is the number of stations currently served by candidate nodeq (excluding station t).

In equation (11), the numerator provides the overall rate achieved bystation t on all available resources for candidate node q, which may bea base station or a relay. Equation (11) is different from equation (3),which assumes that station t is assigned each resource for a fraction ofthe time. The overall rate achieved by station t on all availableresources may be limited by the backhaul capacity of node q. The overallrate may be divided by the number of stations currently served by node qplus one to account for station t being handed over to node q. The ratefrom equation (11) may be an estimated rate with station t beingassigned the same fraction of the available resource as other stationscurrently served by node q.

If candidate node q is not serving any station, then its currenttransmit PSD on all resources may be zero, and the rate estimate fromequation (11) may be zero. This may be addressed in various manners. Inone design, candidate node q may compute and advertise the best initialresource r_(B)(q), which may be determined based on a different utilityfunction, e.g., a utility function with a nominal transmit PSD levelbeing used on resource r. Station t may estimate its rate for candidatenode q by assuming that this resource will be assigned to station tafter association with node q. This assumption may be used for onlycandidate nodes not currently serving any stations.

The rate R(t,q) achieved by station t for candidate node q may be usedto compute local metrics for node q, which may in turn be used to makedecisions on association and resource partitioning. As shown in equation(11), the rate R(t,q) may be affected by (i) other associations, whichmay affect N(q) for the number of stations served by node q, and (ii)resource partitioning, which may affect the spectral efficiency R(t,q,r)of station t on each resource r.

A given node n (e.g., a base station or a relay) may hand out one ormore stations to other nodes and/or may receive (hand in) one or morestations from other nodes. For each station to be handed out, rateR(t,q) may be computed for each candidate node for the station, and theα(t,r) parameter for the station may be set to zero at node n. Localmetrics for each candidate node may be computed by taking into accountthe rate R(t,q) of the station for that candidate node. The resourcespreviously assigned to the station by node n may be re-assigned to otherstations served by node n. For each station to be handed in, rate R(t,n)may be computed for the station for node n, and the α(t,r) parameter forthe station may be set to zero at the current serving node of thestation. Local metrics for node n may be computed by taking into accountthe rate R(t,n) of the station for node n.

The rate in equation (11) may also be used as a metric for initialassociation when station t first accesses the wireless network. Stationt may compute the estimated rate for each detectable node. Station t mayassume an infinite backhaul capacity for each node for which thisinformation is not available. Station t may access the node with thehighest estimated rate and may then become part of the schedulingforecast of that node.

In one design, an adaptive algorithm may be used for joint associationand resource partitioning. The algorithm is adaptive in that it can takeinto consideration the current operating scenario, which may bedifferent for different parts of the wireless network and may alsochange over time. The adaptive algorithm may be performed by each nodein a distributed manner and may attempt to maximize the utility functionover a set of nodes or possibly across the entire wireless network.

FIG. 5 shows a design of a process 500 for performing joint associationand resource partitioning. Process 500 may be performed by each node ina neighbor set for a distributed design. For the first neighbor setdesign described above, the neighbor set may include nodes correspondingto base stations as well as relays. In this design, each base stationand each relay in the neighbor set may perform process 500. For thesecond neighbor set design described above, the neighbor set may includenodes correspond to base stations but not relays. In this design, eachbase station in the neighbor set may perform process 500 and may takeinto account the effects of all relays (if any) served by that basestation. For clarity, process 500 is described below for node p, whichmay be a base station or possibly a relay.

Node p may obtain the current allocation of resources for each node inthe neighbor set (step 512). For the downlink, the allocation ofresources for a node may be defined by a list of transmit PSD levels forthe available resources, one transmit PSD level for each availableresource. The transmit PSD level for each resource may indicate anallowed transmit PSD for the node on the resource. Node p may alsoobtain the current loading of each node in the neighbor set (step 514).The loading of a node may be defined by the number of stations beingserved by the node, the percentage of resources used by the node, etc.Node p may obtain the current allocated resources and the currentloading of the neighbor nodes via the backhaul or through other means.Node p may also advertise its current allocated resources and/or loadingvia the backhaul to the neighbor nodes and possibly over the air for useby stations for initial access or handover decisions.

Node p may determine a list of possible actions related to associationand resource partitioning that can be performed by node p and/orneighbor nodes (step 516). A possible action may cover only association,or only resource partitioning, or both association and resourcepartitioning. A possible action for resource partitioning may cover aspecific allocation of resources for node p as well as a specificallocation of resources for each neighbor node in the neighbor set. Forthe downlink, a possible action for resource partitioning may entailnode p changing its transmit PSD on a particular resource and/or aneighbor node changing its transmit PSD on the resource. A possibleaction for association and resource partitioning may cover a stationbeing handed over to a neighbor node and a grant of an availableresource (e.g., a higher transmit PSD level) to the neighbor node. Somepossible actions for association and resource partitioning are describedbelow.

For the first neighbor set design described above, the list of possibleactions may include possible actions related to resource partitioningfor different nodes as well as possible actions related to resourcepartitioning between the access and backhaul links of relays. Forexample, one possible action may cover (i) node p being allocatedcertain resources and (ii) a first partitioning of the allocatedresources between the access and backhaul links of relay z. Anotherpossible action may cover (i) node p being allocated the same resourcesand (ii) a second partitioning of the allocated resources between theaccess and backhaul links of relay z.

For the second neighbor set design described above, the list of possibleactions may include possible actions related to resource partitioningfor different nodes. For a given possible action with node p beingallocated certain resources, different possible partitioning of theallocated resources between node p and relay z may be evaluated. Theaccess/backhaul partitioning with the best performance may be used tocompute the local metric for node p for the possible action.

The list of possible actions may include (i) standard actions that maybe evaluated periodically without any explicit request and/or (ii)on-demand actions that may be evaluated in response to requests fromneighbor nodes. The standard actions may involve one resource and eitherone or two nodes. The on-demand actions may involve handover ofstations, allocation for more than one resource (e.g., for handovernegotiation), actions involving more than one neighbor node (e.g., forresource partitioning), etc.

Node p may compute local metrics for different possible actions (block518). For example, a local metric based on the sum rate utility functionin equation (1) may indicate an overall rate achieved by node p for aparticular action a and may be computed as follows:

$\begin{matrix}{{{U\left( {p,a} \right)} = {\sum\limits_{{S{(t)}} = p}\;{R\left( {t,a} \right)}}},} & {{Eq}\mspace{14mu}(12)}\end{matrix}$where R(t,a) is the rate achieved by station t for action a, and

U(p,a) is a local metric for node p for action a.

The rate R(t,a) for each station may be computed as shown in equations(2) and (3), where PSD(p,r) and PSD(q,r) may be dependent on the listsof transmit PSD levels for nodes p and q, respectively, associated withpossible action a. In general, the local metric for node p for eachpossible action may be dependent on the utility function.

The local metrics for different possible actions may be used by node pas well as the neighbor nodes to compute overall metrics for differentpossible actions. Node p may send its computed local metrics U(p,a), fora ε A, to the neighbor nodes, where A denotes the list of possibleactions (block 520). Node p may also receive local metrics U(q,a), for aε A, from each neighbor node q in the neighbor set (block 522). Node pmay compute overall metrics for different possible actions based on itscomputed local metrics and the received local metrics (block 524). Forexample, an overall metric based on the sum rate utility function inequation (1) may be computed for each possible action a, as follows:

$\begin{matrix}{{{V(a)} = {{U\left( {p,a} \right)} + {\sum\limits_{q \in \;{{{NS}{(p)}}\backslash{\{ p\}}}}^{\;}\;{U\left( {q,a} \right)}}}},} & {{Eq}\mspace{14mu}(13)}\end{matrix}$where V(a) is an overall metric for possible action a. The summation inequation (13) is over all neighbor nodes in the neighbor set except fornode p.

After completing the metric computation, node p may select the actionwith the best overall metric (block 526). Each neighbor node maysimilarly compute overall metrics for different possible actions and mayalso select the action with the best overall metric. Node p and theneighbor nodes should select the same action if they operate on the sameset of local metrics. Each node may then operate based on the selectedaction, without having to communicate with one another regarding theselected action. However, node p and its neighbor nodes may operate ondifferent local metrics and may obtain different best overall metrics.This may be the case, for example, if node p and its neighbor nodes havedifferent neighbor sets. In this case, node p may negotiate with theneighbor nodes to determine which action to take. This may entailexchanging overall metrics for some promising actions between the nodesand selecting the action that can provide good performance for as manynodes as possible.

Regardless of how the best action is selected, the selected action isassociated with a specific allocation of resources for node p andpossibly specific association updates for node p. Node p may performhandovers of stations based on the association updates, if any. Node pmay communicate with its stations based on the resources allocated tonode p by the selected action (block 528). The allocated resources maybe defined by a list of transmit PSD levels, one specific transmit PSDlevel for each available resource. Node p may use the specified transmitPSD level for each available resource.

There may be a large number of possible actions to evaluate for anexhaustive search to find the best action. The number of possibleactions to evaluate may be reduced in various manners. In one design,each available resource may be treated independently, and a given actionmay change the transmit PSD level of only one resource. In anotherdesign, the number of nodes that can adjust their transmit PSD levels ona given resource for a given action may be limited. In yet anotherdesign, the transmit PSD for a given node on a given resource may beeither increased or decreased by one level at a time. The number ofpossible actions may also be reduced via other simplifications.

In one design, a list of possible actions that may lead to good overallmetrics may be evaluated. Possible actions that are unlikely to providegood overall metrics may be skipped in order to reduce computationcomplexity. For example, having both node p and a neighbor node increasetheir target transmit PSD levels on the same resource will likely resultin extra interference on the resource, which may degrade performance forboth nodes. This possible action may thus be skipped. As anotherexample, having node p hand out a station to neighbor node q and alsoclaim a resource from node q will likely result in a lower overallmetric. This possible action may also be skipped.

Table 2 lists different types of actions for resource partitioning thatmay be evaluated, in accordance with one design.

TABLE 2 Action Types for Resource Partitioning Action Type Descriptionp-C-r Node p claims resource r and increases its transmit PSD by onelevel on resource r. p-B-r Node p blanks resource r and decreases itstransmit PSD by one level on resource r. p-R-r-Q Node p requestsresource r from one or more neighbor nodes in set Q and asks theneighbor node(s) in set Q to decrease their transmit PSD by one level onresource r. p-G-r-Q Node p grants resource r to one or more neighbornodes in set Q and tells the neighbor node(s) in set Q to increase theirtransmit PSD by one level on resource r. p-CR-r-Q Node p claims andrequests resource r from one or more neighbor nodes in set Q and (i)increases its transmit PSD by one level on resource r and (ii) asks theneighbor node(s) in set Q to decrease their transmit PSD by one level onresource r. p-BG-r-Q Node p blanks and grants resource r to one or moreneighbor nodes in set Q and (i) decreases its transmit PSD by one levelon resource r and (ii) tells the neighbor node(s) in set Q to increasetheir transmit PSD by one level on resource r.

Each action type in Table 2 may be associated with a set of possibleactions of that type. For each action type involving only node p, Kpossible actions may be evaluated for K available resources. For eachaction type involving both node p and one or more neighbor nodes in setQ, multiple possible actions may be evaluated for each availableresource, with the number of possible actions being dependent on thesize of the neighbor set, the size of set Q, etc. In general, set Q mayinclude one or more neighbor nodes and may be limited to a small value(e.g., 2 or 3) in order to reduce the number of possible actions toevaluate.

Table 3 lists different types of actions for association and resourcepartitioning that may be evaluated, in accordance with one design. Thefirst two rows of Table 3 cover action types for only association. Thelast two rows of Table 3 cover action types for both association andresource partitioning.

TABLE 3 Action Types for Association and Resource Partitioning ActionType Description p-HON-t-q Node p hands out station t to neighbor node qwithout granting any resources. p-HIN-t-q Node p receives (or hands in)station t from neighbor node q without receiving any resources.p-HOG-T-Q-R Node p hands out one or more stations in set T to one ormore neighbor nodes in set Q and also grants one or more resources inset R. p-HIR-T-Q-R Node p receives one or more stations in set T fromone or more neighbor nodes in set Q and also requests one or moreresources in set R.

Each action type in Table 3 may be associated with a set of possibleactions of that type. For the hand out or hand in action type involvingonly one station t, L possible actions may be evaluated for L candidatestations. The candidate stations may be identified based on variousmetrics such as channel difference, relative strength, etc. Channeldifference may be defined as the ratio of (i) a channel gain between astation and a dominant interferer to (ii) a channel gain between thestation and a serving node. The number of candidate stations may belimited to reduce computation complexity. For example, L stations withthe L highest channel differences may be selected as candidate stations.Stations located close to their serving nodes may be omitted fromevaluation for association updates. Set Q may be limited to a smallnumber of neighbor nodes, set T may be limited to a small number ofcandidate stations, and set R may be limited to a small number ofresources in order to reduce the number of possible actions to evaluate.

Tables 2 and 3 list some types of actions that may be evaluated forjoint association and resource partitioning. Fewer, more and/ordifferent action types may also be evaluated.

Node p may compute local metrics for different possible actions based on(i) pilot measurements from stations served by node p, (ii) theallocated resources (e.g., the lists of transmit PSD levels) for node pand neighbor nodes associated with these possible actions, and (iii) thepartitioning between the access and backhaul links for the possibleactions. A relay served by node p may be treated in similar manner as astation for rate computation. For each possible action, node p may firstcompute the spectral efficiency R(t,r) of each station served by node pon each resource r, e.g., as shown in equation (3). The spectralefficiency computation may be dependent on a scheduling forecast toobtain the α(t,r) values for the stations served by node p. PSD(p,r) andPSD(q,r) in equation (3) may be obtained from the lists of transmit PSDlevels for nodes p and q, respectively. G(p,t) and G(q,t) is equation(3) may be obtained from pilot measurements from station t for nodes pand q, respectively. The rate for each station may be computed based onthe spectral efficiencies of that station on all resources, e.g., asshown in equation (2). A local metric for the possible action may thenbe computed based on the rates for all stations served by node p, e.g.,as shown in equation (1) for the sum rate utility function.

Node p may exchange local metrics with the neighbor nodes in theneighbor set (e.g., via the backhaul) to enable each node to computeoverall metrics for different possible actions. In one design, localmetrics for possible actions involving only node p may be sent to allneighbor nodes in the neighbor set. Local metrics for possible actionsinvolving neighbor node q may be sent to only node q. Local metrics forpossible actions involving neighbor nodes in set Q may be sent to eachnode in set Q. Node p may compute overall metrics for different possibleactions based on the computed local metrics and the received localmetrics.

For clarity, joint association and resource partitioning has beenspecifically described for the downlink. Unified resource partitioning(without association) to allocate the available resources to nodes andto the access and backhaul links may be performed for the downlink insimilar manner. In this case, possible actions related to resourcepartitioning may be evaluated, and possible actions related toassociation may be omitted.

Unified resource partitioning or joint association and resourcepartitioning may also be performed for the uplink in similar manner. Inone design, a set of target interference-over-thermal (IoT) levels maybe used for resource partitioning on the uplink in similar manner as theset of PSD levels for the downlink. One target IoT level may be selectedfor each resource on the uplink, and transmissions from each station oneach resource may be controlled so that the actual IoT on that resourceat each neighbor node in the active set of the station is at or belowthe target IoT level for that resource at the neighbor node. A utilityfunction may be defined to quantify performance of data transmission onthe uplink and may be any of the functions described above, e.g., afunction of the sum of user rates. The rate of each station on theuplink may be a function of transmit power, channel gain, target IoTlevel, etc. Local metrics and overall metrics may be computed fordifferent possible actions based on the utility function. Each possibleaction may be associated with a list of target IoT levels for allavailable resources for each node in a neighbor set. The possible actionwith the best overall metric may be selected for use.

FIG. 6 shows a design of a process 600 for supporting communication.Process 600 may be performed by a node or some other entity. Resourcepartitioning may be performed to allocate available resources to a setof nodes and to access and backhaul links of at least one relay (block612). Resources allocated to a node in the set of nodes or a relay amongthe at least one relay may be determined based on the resourcepartitioning (block 614).

In one design, the resource partitioning in block 612 may be performedin two steps. In the first step, resource partitioning may be performedto allocate the available resources to the set of nodes. Resourcesallocated to a serving node of the relay may be determined based on thisresource partitioning. In the second step, resource partitioning may beperformed to allocate the resources allocated to the serving node to theaccess and backhaul links of the relay. In another design, the resourcepartitioning in block 612 may be performed in a single step toconcurrently allocate the available resources to the set of nodes and tothe access and backhaul links of the at least one relay.

In one design, the set of nodes may include base stations and the atleast one relay. Resource partitioning may be performed based on metricscomputed for each node in the set of nodes. The metrics for each nodemay be indicative of the performance of that node. In another design,the set of nodes may include at least one serving node for the at leastone relay and may exclude the at least one relay. Resource partitioningmay be performed based on metrics computed for each node in the set ofnodes. The metrics for each serving node may be indicative of theperformance of the serving node as well as all relays served by theserving node.

In one design, resource partitioning may be performed by limiting abackhaul rate for a relay to an access capacity of the relay, e.g., asshown in equation (10). The access capacity of the relay may be variableand dependent on the resources allocated to the access link of therelay. In another design, resource partitioning may be performed bylimiting the total rate for all stations served by the relay to abackhaul capacity of the relay, e.g., as shown in equation (9). Thebackhaul capacity may be variable and dependent on the resourcesallocated to the backhaul link of the relay.

In one design, resource partitioning may be performed by modeling therelay as a station by the serving node of the relay. In another design,resource partitioning may be performed by modeling the relay as Mstations each having a rate of R/M, where M is the number of stationsserved by the relay and R is the total rate of the M stations.

In one design, association for at least one station may be performed. Atleast one serving node for the at least one station may be determinedbased on the association. Association and resource partitioning may beperformed jointly by evaluating a plurality of possible actions relatedto association and resource partitioning, as described above.

The available resources may be for time units, frequency units,time-frequency units, etc. In one design, the available resources may befor the downlink. In this design, the resources allocated to a node or arelay may be given by a list of transmit PSD levels, one transmit PSDlevel for each available resource. In another design, the availableresources may be for the uplink. In this design, the resources allocatedto a node or a relay may be given by a list of target IoT levels, onetarget IoT level for each available resource. The allocated resourcesmay also be given in other manners.

FIG. 7 shows a design of an apparatus 700 for supporting communication.Apparatus 700 includes a module 712 to perform resource partitioning toallocate available resources to a set of nodes and to access andbackhaul links of at least one relay, and a module 714 to determineresources allocated to a node in the set of nodes or a relay among theat least one relay based on the resource partitioning.

FIG. 8 shows a design of a process 800 for performing unified resourcepartitioning, which may be used for blocks 612 and 614 in FIG. 6. A nodemay compute local metrics for a plurality of possible actions related toresource partitioning for a set of nodes and resource partitioningbetween the access and backhaul links of at least one relay (block 812).The node may send the computed local metrics to at least one neighbornode in the set of nodes to enable the neighbor node(s) to computeoverall metrics for the plurality of possible actions (block 814). Thenode may receive local metrics for the plurality of possible actionsfrom the at least one neighbor node (block 816). The node may determineoverall metrics for the plurality of possible actions based on thecomputed local metrics and the received local metrics for these possibleactions (block 818). The node may select one of the plurality ofpossible actions based on the overall metrics for these possible actions(block 820). The node may determine resources allocated to the set ofnodes and resources allocated to the access and backhaul links of the atleast one relay based on the selected action (block 822).

In one design, the plurality of possible actions may include possibleactions related to association for at least one station. At least oneserving node for the at least one station may be determined based on theoverall metrics for the plurality of possible actions.

In one design of block 812, the node may compute a local metric for eachpossible action as follows. The node may determine allocation ofavailable resources to the set of nodes for the possible action. Forexample, the node may determine (i) a list of transmit PSD levels foreach node for the downlink or (ii) a list of target IoT levels for eachnode for the uplink. The node may also determine allocation of resourcesbetween the access and backhaul links for the possible action. The nodemay determine at least one rate for at least one station communicatingwith the node based on the allocation of the available resources to theset of nodes and to the access and backhaul links. The node may thendetermine the local metric for the possible action based on the at leastone rate for the at least one station, e.g., as shown in equation (1).In general, the local metric for each possible action may be computedbased on a function of rate, or latency, or queue size, or some otherparameter, or a combination thereof. The local metric for each possibleaction may also be computed based on a function of sum of rates, orminimum of rates, or sum of quantities determined based on rates, etc.

The description above is for a distributed design in which each node inthe set of nodes may compute and exchange local and overall metrics fordifferent possible actions. For a centralized design, a designatedentity may compute local and overall metrics for different possibleactions and may select the best action.

FIG. 9 shows a design of a process 900 for supporting communication.Process 900 may be performed by a node or some other entity. Metrics fora plurality of possible actions related to association involving atleast one relay may be obtained (block 912). The plurality of possibleactions may comprise (i) possible actions for handing out one or morestations from a node to neighbor nodes and/or (ii) possible actions forhanding in one or more stations from the neighbor nodes to the node. Atleast one serving node for at least one station may be determined basedon the metrics for the plurality of possible actions (block 914). The atleast one serving node and the at least one station may comprise atleast one relay. For example, the at least one serving node may comprisea base station, and the at least one station may comprise a relay. Asanother example, the at least one serving node may comprise a relay, andthe at least one station may comprise a UE.

In one design, metrics (e.g., rates, local metrics, and/or overallmetrics) for a relay may be computed based on resources allocated to theaccess and backhaul links of the relay. In another design, metrics forthe relay may be computed based on an access capacity and a backhaulcapacity of the relay. For both designs, the metrics may be used to (i)select a serving node for the relay and/or (ii) determine whether toselect the relay as a serving node for a UE.

FIG. 10 shows a design of an apparatus 1000 for supportingcommunication. Apparatus 1000 includes a module 1012 to obtain metricsfor a plurality of possible actions related to association involving atleast one relay, and a module 1014 to determine at least one servingnode for at least one station based on the metrics for the plurality ofpossible actions. The at least one serving node and the at least onestation may comprise the at least one relay.

FIG. 11 shows a design of a process 1100 for supporting communication.Process 1100 may be performed by a relay (as described below) or by someother entity. The relay may determine resources allocated to the relaybased on resource partitioning to allocate available resources to a setof nodes and to access and backhaul links of at least one relay (block1112). The relay may be one of the at least one relay. The relay maycommunicate with at least one station on the resources allocated to therelay (block 1114).

In one design, the set of nodes may include the relay. In this design,the relay may perform resource partitioning with other nodes in the setof nodes to determine the resources allocated to the relay. In anotherdesign, the set of nodes may exclude the relay. In this design, therelay may exchange information used for resource partitioning (e.g.,access capacity, number of stations served by the relay, etc.) with aserving node of the relay. The serving node may perform resourcepartitioning based on the exchanged information.

In one design, the relay may determine an access capacity of the relay.Resource partitioning may be performed by limiting a backhaul rate forthe relay to the access capacity of the relay. In another design, therelay may determine a backhaul capacity of the relay and may limit thetotal rate of the at least one station based on the backhaul capacity ofthe relay.

In one design, the relay may further determine a station handed out fromthe relay or handed in to the relay. In one design, handover of thestation may be determined based on association performed jointly withresource partitioning by evaluating a plurality of possible actionsrelated to association and resource partitioning.

FIG. 12 shows a design of an apparatus 1200 for exchanging data in awireless communication system. Apparatus 1200 includes a module 1212 todetermine resources allocated to a relay based on resource partitioningto allocate available resources to a set of nodes and to access andbackhaul links of at least one relay, the relay being one of the atleast one relay, and a module 1214 to communicate with at least onestation by the relay on the resources allocated to the relay

FIG. 13 shows a design of a process 1300 for communicating in a wirelessnetwork. Process 1300 may be performed by a UE (as described below) orby some other entity. The UE may make pilot measurements for nodesdetectable by the UE (block 1312). The pilot measurements may be used todetermine an active set for the UE, to compute metrics for associationand/or resource partitioning, and/or for other purposes. The UE mayreceive an assignment of at least one resource from a node (block 1314).Resource partitioning may be performed to allocate available resourcesto a set of nodes and to access and backhaul links of at least onerelay. The at least one resource assigned to the UE may be from a subsetof the available resources allocated to the node by the resourcepartitioning. In one design, the node may be one of the at least onerelay, and the subset of the available resources allocated to the nodemay be for the access link of the node/relay.

The UE may communicate with the node on the at least one resource (block1316). In one design, for the downlink, the UE may receive datatransmission on the at least one resource from the node. The datatransmission may be sent by the node on each of the at least oneresource at a transmit PSD level allowed for the node on the resource.In another design, for the uplink, the UE may send data transmission onthe at least one resource to the node. The UE may send the datatransmission on each of the at least one resource at a transmit powerlevel determined based on at least one target IoT level for at least oneneighbor node on the resource.

FIG. 14 shows a design of an apparatus 1400 for supportingcommunication. Apparatus 1400 includes a module 1412 to make pilotmeasurements for nodes detectable by a UE, a module 1414 to receive anassignment of at least one resource from a node at the UE, and a module1416 to communicate with the node on the at least one resource by theUE.

The modules in FIGS. 7, 10, 12 and 14 may comprise processors,electronic devices, hardware devices, electronic components, logicalcircuits, memories, software codes, firmware codes, etc., or anycombination thereof.

FIG. 15 shows a block diagram of a design of a node 1500 and a station1550. Node 1500 may be a base station or a relay. Station 1550 may be arelay or a UE. Node 1500 may be equipped with T antennas 1534 a through1534 t, and station 1550 may be equipped with R antennas 1552 a through1552 r, where in general T≧1 and R≧1.

At node 1500, a transmit processor 1520 may receive data from a datasource 1512 for one or more stations and control information from acontroller/processor 1540. Processor 1520 may process (e.g., encode,interleave, and modulate) the data and control information to obtaindata symbols and control symbols, respectively. Processor 1520 may alsogenerate pilot symbols for pilot or reference signal. A transmit (TX)multiple-input multiple-output (MIMO) processor 1530 may perform spatialprocessing (e.g., precoding) on the data symbols, the control symbols,and/or the pilot symbols, if applicable, and may provide T output symbolstreams to T modulators (MODs) 1532 a through 1532 t. Each modulator1532 may process a respective output symbol stream (e.g., for OFDM,etc.) to obtain an output sample stream. Each modulator 1532 may furtherprocess (e.g., convert to analog, amplify, filter, and upconvert) theoutput sample stream to obtain a downlink signal. T downlink signalsfrom modulators 1532 a through 1532 t may be transmitted via T antennas1534 a through 1534 t, respectively.

At station 1550, antennas 1552 a through 1552 r may receive the downlinksignals from node 1500 and may provide received signals to demodulators(DEMODs) 1554 a through 1554 r, respectively. Each demodulator 1554 maycondition (e.g., filter, amplify, downconvert, and digitize) itsreceived signal to obtain input samples. Each demodulator 1554 mayfurther process the input samples (e.g., for OFDM, etc.) to obtainreceived symbols. A MIMO detector 1556 may obtain received symbols fromall R demodulators 1554 a through 1554 r, perform MIMO detection on thereceived symbols if applicable, and provide detected symbols. A receiveprocessor 1558 may process (e.g., demodulate, deinterleave, and decode)the detected symbols, provide decoded data for station 1550 to a datasink 1560, and provide decoded control information to acontroller/processor 1580.

On the uplink, at station 1550, a transmit processor 1564 may receiveand process data from a data source 1562 and control information fromcontroller/processor 1580. Processor 1564 may also generate pilotsymbols for pilot or reference signal. The symbols from transmitprocessor 1564 may be precoded by a TX MIMO processor 1566 ifapplicable, further processed by modulators 1554 a through 1554 r (e.g.,for SC-FDM, OFDM, etc.), and transmitted to node 1500. At node 1500, theuplink signals from station 1550 may be received by antennas 1534,processed by demodulators 1532, detected by a MIMO detector 1536 ifapplicable, and further processed by a receive processor 1538 to obtaindecoded data and control information sent by station 1550. Processor1538 may provide the decoded data to a data sink 1539 and the decodedcontrol information to controller/processor 1540.

Controllers/processors 1540 and 1580 may direct the operation at node1500 and station 1550, respectively. A channel processor 1584 may makepilot measurements, which may be used to determine an active set forstation 1550 and to compute channel gains, rates, metrics, etc.Processor 1540 and/or other processors and modules at node 1500 mayperform or direct process 500 in FIG. 5, process 600 in FIG. 6, process800 in FIG. 8, process 900 in FIG. 9, process 1100 in FIG. 11, and/orother processes for the techniques described herein. Processor 1580and/or other processors and modules at station 1550 may perform ordirect process 1100 in FIG. 11, process 1300 in FIG. 13, and/or otherprocesses for the techniques described herein. Memories 1542 and 1582may store data and program codes for node 1500 and station 1550,respectively. A scheduler 1544 may schedule stations for datatransmission on the downlink and/or uplink.

Those of skill in the art would understand that information and signalsmay be represented using any of a variety of different technologies andtechniques. For example, data, instructions, commands, information,signals, bits, symbols, and chips that may be referenced throughout theabove description may be represented by voltages, currents,electromagnetic waves, magnetic fields or particles, optical fields orparticles, or any combination thereof.

Those of skill would further appreciate that the various illustrativelogical blocks, modules, circuits, and algorithm steps described inconnection with the disclosure herein may be implemented as electronichardware, computer software, or combinations of both. To clearlyillustrate this interchangeability of hardware and software, variousillustrative components, blocks, modules, circuits, and steps have beendescribed above generally in terms of their functionality. Whether suchfunctionality is implemented as hardware or software depends upon theparticular application and design constraints imposed on the overallsystem. Skilled artisans may implement the described functionality invarying ways for each particular application, but such implementationdecisions should not be interpreted as causing a departure from thescope of the present disclosure.

The various illustrative logical blocks, modules, and circuits describedin connection with the disclosure herein may be implemented or performedwith a general-purpose processor, a digital signal processor (DSP), anapplication specific integrated circuit (ASIC), a field programmablegate array (FPGA) or other programmable logic device, discrete gate ortransistor logic, discrete hardware components, or any combinationthereof designed to perform the functions described herein. Ageneral-purpose processor may be a microprocessor, but in thealternative, the processor may be any conventional processor,controller, microcontroller, or state machine. A processor may also beimplemented as a combination of computing devices, e.g., a combinationof a DSP and a microprocessor, a plurality of microprocessors, one ormore microprocessors in conjunction with a DSP core, or any other suchconfiguration.

The steps of a method or algorithm described in connection with thedisclosure herein may be embodied directly in hardware, in a softwaremodule executed by a processor, or in a combination of the two. Asoftware module may reside in RAM memory, flash memory, ROM memory,EPROM memory, EEPROM memory, registers, hard disk, a removable disk, aCD-ROM, or any other form of storage medium known in the art. Anexemplary storage medium is coupled to the processor such that theprocessor can read information from, and write information to, thestorage medium. In the alternative, the storage medium may be integralto the processor. The processor and the storage medium may reside in anASIC. The ASIC may reside in a user terminal. In the alternative, theprocessor and the storage medium may reside as discrete components in auser terminal.

In one or more exemplary designs, the functions described may beimplemented in hardware, software, firmware, or any combination thereof.If implemented in software, the functions may be stored on ortransmitted over as one or more instructions or code on acomputer-readable medium. Computer-readable media includes both computerstorage media and communication media including any medium thatfacilitates transfer of a computer program from one place to another. Astorage media may be any available media that can be accessed by ageneral purpose or special purpose computer. By way of example, and notlimitation, such computer-readable media can comprise RAM, ROM, EEPROM,CD-ROM or other optical disk storage, magnetic disk storage or othermagnetic storage devices, or any other medium that can be used to carryor store desired program code means in the form of instructions or datastructures and that can be accessed by a general-purpose orspecial-purpose computer, or a general-purpose or special-purposeprocessor. Also, any connection is properly termed a computer-readablemedium. For example, if the software is transmitted from a website,server, or other remote source using a coaxial cable, fiber optic cable,twisted pair, digital subscriber line (DSL), or wireless technologiessuch as infrared, radio, and microwave, then the coaxial cable, fiberoptic cable, twisted pair, DSL, or wireless technologies such asinfrared, radio, and microwave are included in the definition of medium.Disk and disc, as used herein, includes compact disc (CD), laser disc,optical disc, digital versatile disc (DVD), floppy disk and blu-ray discwhere disks usually reproduce data magnetically, while discs reproducedata optically with lasers. Combinations of the above should also beincluded within the scope of computer-readable media.

The previous description of the disclosure is provided to enable anyperson skilled in the art to make or use the disclosure. Variousmodifications to the disclosure will be readily apparent to thoseskilled in the art, and the generic principles defined herein may beapplied to other variations without departing from the spirit or scopeof the disclosure. Thus, the disclosure is not intended to be limited tothe examples and designs described herein but is to be accorded thewidest scope consistent with the principles and novel features disclosedherein.

What is claimed is:
 1. A method for wireless communication, comprising:obtaining, using at least one network entity, loading informationcorresponding to at least one neighbor node; obtaining, using the atleast one network entity, metrics for a plurality of possible actionsrelated to association involving at least one relay; determining, usingthe at least one network entity, at least one serving node for at leastone station based on said loading information and the metrics for theplurality of possible actions; communicating, using the at least oneserving node, with the at least one station; wherein the at least oneserving node is one of a base station or the at least one relay; whereinthe metrics for the at least one relay are based on at least one of:resources allocated to access and backhaul links of the at least onerelay, an access capacity of the at least one relay, or a backhaulcapacity of the at least one relay; and wherein said network entity isone of said base station or said at least one relay, said at least onerelay operating as a network node capable of communicating with said atleast one station on an access link.
 2. The method of claim 1, whereinthe plurality of possible actions comprise possible actions for handingout one or more stations from a node to neighbor nodes, or possibleactions for handing in one or more stations from the neighbor nodes tothe node, or both.
 3. The method of claim 1, wherein the at least oneserving node comprises a base station and the at least one stationcomprises a relay, or the at least one serving node comprises a relayand the at least one station comprises a user equipment (UE), or both.4. The method of claim 1, wherein the metrics for the at least one relayare based on resources allocated to access and backhaul links of the atleast one relay.
 5. The method of claim 1, wherein the metrics for theat least one relay are based on an access capacity of the at least onerelay.
 6. The method of claim 1, wherein said loading informationindicates a number of stations currently served by the at least oneneighbor node.
 7. An apparatus for wireless communication, comprising:means for obtaining loading information corresponding to at least oneneighbor node and for obtaining metrics for a plurality of possibleactions related to association involving at least one relay; means fordetermining at least one serving node for at least one station based onsaid loading information and the metrics for the plurality of possibleactions; means for communicating with the at least one station; whereinthe at least one serving node is one of a base station or the at leastone relay; wherein the metrics for the at least one relay are based onat least one of: resources allocated to access and backhaul links of theat least one relay, an access capacity of the at least one relay, or abackhaul capacity of the at least one relay; and wherein said apparatusis a network entity and is one of said base station or said at least onerelay, said at least one relay operating as a network node capable ofcommunicating with said at least one station on an access link.
 8. Theapparatus of claim 7, wherein the plurality of possible actions comprisepossible actions for handing out one or more stations from a node toneighbor nodes, or possible actions for handing in one or more stationsfrom the neighbor nodes to the node, or both.
 9. An apparatus forwireless communication, comprising: a memory; at least one processorcoupled to the memory, said at least one processor being configured to:obtain loading information corresponding to at least one neighbor node;obtain metrics for a plurality of possible actions related toassociation involving at least one relay, to store the metrics in thememory; determine at least one serving node for at least one stationbased on said loading information and the metrics for the plurality ofpossible actions; wherein the at least one serving node is one of a basestation or the at least one relay; wherein the metrics for the at leastone relay are based on at least one of: resources allocated to accessand backhaul links of the at least one relay, an access capacity of theat least one relay, or a backhaul capacity of the at least one relay;and wherein said apparatus is a network entity and is one of said basestation or said at least one relay, said at least one relay operating asa network node capable of communicating with said at least one stationon an access link.
 10. A non-transitory computer-readable medium of anapparatus, the non-transitory computer-readable medium storing computerexecutable code, comprising: code for causing at least one computer toobtain loading information corresponding to at least one neighbor node;code for causing the at least one computer to obtain metrics for aplurality of possible actions related to association involving at leastone relay; code for causing the at least one computer to determine atleast one serving node for at least one station based on said loadinginformation and the metrics for the plurality of possible actions; codefor causing the at least one computer to communicate with the at leastone station; wherein the at least one serving node is one of a basestation or the at least one relay; wherein the metrics for the at leastone relay are based on at least one of: resources allocated to accessand backhaul links of the at least one relay, an access capacity of theat least one relay, or a backhaul capacity of the at least one relay;and wherein said apparatus is a network entity and is one of said basestation or said at least one relay, said at least one relay operating asa network node capable of communicating with said at least one stationon an access link.